In this study, we investigated the effects of PAHs and dioxin on mRNA and plasma protein expression using genomic and proteomic analysis for automobile emission inspectors and waste incineration workers. About 54 workers from automobile emission inspection offices, 31 workers from waste incinerating company and 84 unexposed healthy subjects were enrolled in this study. Urine and air samples were collected and analyzed by HPLC and GC/MS. Comet assays were carried out to evaluate any DNA damage in mononuclear and polynuclear cells. A significant difference in Olive tail moments in mononuclear cells was observed between exposed and control subjects (P <0.0001). To examine the differences of the gene expression profile in automobile emission inspectors and waste incineration workers, radioactive complementary DNA microarrays were used to evaluate changes in the expression of 1,152 total genes. The gene expression profiles showed that 11 genes were up-regulated and 4 genes were down-regulated in waste incinerating workers as compared with controls. Plasma proteins were analyzed by 2-dimentional electrophoresis with pH 3-10 NL IPG Dry strip. The protein expression profiles showed that 8 proteins were up- regulated and 1 protein, haptoglobin, was down- regulated in automobile emission inspectors and waste incineration workers. Serum paraoxonase/ arylesterase was found only in the plasma of waste incineration workers. The expression of genes and proteins involved in oxidative stress were up-regulated in both automobile emission inspectors and waste incineration workers. Several proteins, such as transthyrethin, sarcolectin and haptoglobin, that were highly up- or down-regulated, could serve as biological monitoring markers for future study.
Adult ; Aged ; Biological Markers/analysis ; DNA Fragmentation ; Environmental Monitoring/*methods ; Gene Expression Profiling ; Genetic Markers ; Genomics ; Humans ; *Incineration ; Middle Aged ; Naphthols/urine ; Occupational Exposure/analysis ; Oligonucleotide Array Sequence Analysis ; Polycyclic Hydrocarbons, Aromatic/analysis/*toxicity ; Proteomics ; Pyrenes/analysis ; Research Support, Non-U.S. Gov't ; Tetrachlorodibenzodioxin/analysis/*toxicity ; *Vehicle Emissions

OBJECTIVES: The purpose of this study was to evaluate the exposure to arsenic in preventive maintenance (PM) engineers in a semiconductor industry by detecting speciated inorganic arsenic metabolites in the urine. METHODS: The exposed group included 8 PM engineers from the clean process area and 13 PM engineers from the ion implantation process area; the non-exposed group consisted of 14 office workers from another company who were not occupationally exposed to arsenic. A spot urine specimen was collected from each participant for the detection and measurement of speciated inorganic arsenic metabolites. Metabolites were separated by high performance liquid chromatography-inductively coupled plasma spectrometry-mass spectrometry. RESULTS: Urinary arsenic metabolite concentrations were 1.73 g/L, 0.76 g/L, 3.45 g/L, 43.65 g/L, and 51.32 g/L for trivalent arsenic (As3+), pentavalent arsenic (As5+), monomethylarsonic acid (MMA), dimethylarsinic acid (DMA), and total inorganic arsenic metabolites (As3+ + As5+ + MMA + DMA), respectively, in clean process PM engineers. In ion implantation process PM engineers, the concentrations were 1.74 g/L, 0.39 g/L, 3.08 g/L, 23.17 g/L, 28.92 g/L for As3+, As5+, MMA, DMA, and total inorganic arsenic metabolites, respectively. Levels of urinary As3+, As5+, MMA, and total inorganic arsenic metabolites in clean process PM engineers were significantly higher than that in the non-exposed group. Urinary As3+ and As5+ levels in ion implantation process PM engineers were significantly higher than that in non-exposed group. CONCLUSION: Levels of urinary arsenic metabolites in PM engineers from the clean process and ion implantation process areas were higher than that in office workers. For a complete assessment of arsenic exposure in the semiconductor industry, further studies are needed.
Arsenic* ; Cacodylic Acid ; Occupations ; Plants* ; Plasma ; Semiconductors* ; Spectrum Analysis

OBJECTIVES: This study was conducted to examine the relationship between crude oil exposure and physical symptoms among residents participating in clean-up work associated with the Hebei Spirit oil spill, 2007 in Korea. METHODS: A total of 288 residents responded to a questionnaire regarding subjective physical symptoms, sociodemographic characteristics and clean-up activities that occurred between two and eight weeks after the accident. Additionally, the urine of 154 of the respondents was analyzed for metabolites of volatile organic compounds (VOCs) and polycyclic aromatic hydrocarbons (PAHs) and heavy metals. To compare the urinary levels of exposure biomarkers, the urine of 39 inland residents who were not directly exposed to the oil spill were analyzed. RESULTS: Residents exposed to oil remnants through clean-up work showed associations between physical symptoms and the exposure levels defined in various ways, including days of work, degree of skin contamination, and levels of some urinary exposure biomarkers of VOCs, metabolites and metals, although no major abnormalities in urinary exposure biomarkers were observed. CONCLUSIONS: This study provides evidence of a relationship between crude oil exposure and acute human health effects and suggests the need for follow-up to evaluate the exposure status and long-term health effects of clean-up participants.
Follow-Up Studies ; Humans ; Metals ; Metals, Heavy ; Petroleum ; Petroleum Pollution ; Polycyclic Hydrocarbons, Aromatic ; Skin ; Volatile Organic Compounds ; Biomarkers ; Surveys and Questionnaires

OBJECTIVES: To identify any association between implementing smoking regulation policies and workers' urine cotinine concentration levels in Korea. METHODS: From the first stage of the Korean National Environmental Health Survey conducted by the National Institute of Environmental Research from 2009 to 2011, 2,475 non-smoking workers selected. We analyzed the trend in the changes of cotinine concentration in urine using the general linear model and linear regression, in various jobs as categorized by the National Center for Health Statistics (NCHS) and Korea Standard Classification of Occupations (KSCO). RESULTS: The urine cotinine concentration tended to decrease every year (2.91 ng/ml in 2009, 2.12 ng/ml in 2010, and 1.31 ng/ml in 2011), showing a decreasing trend (P < 0.001). The total subjects' decreased cotinine concentration in urine between 2009 and 2011 was 2.72 ng/ml (54.1 % relative decrease). The changes in each subgroup's urine cotinine concentration ranged from 1.59 to 6.03 ng/ml (33.2 to 77.5 %). All groups except for the managerial group (n = 49), which had a small sample size, had statistically significant negative regression coefficients (p < 0.05). The ranges of the decrease in urine cotinine were 2.75 ng/ml (53.6 %) for males and 2.72 ng/ml (54.9 %) for females. The negative slope in urine cotinine level was statistically significantly greater in men than women. The changes in urine cotinine by occupation as classified by the NCHS occupational categories ranged from 2.43 to 3.36 ng/ml (46.6 to 61.5 % relative decrease). The negative slopes in urine cotinine levels of the white-collar and farm workers were statistically significantly greater than those of the service workers and blue-collar workers. The change by occupation as classified by the KSCO ranged from 1.59 to 6.03 ng/ml (a 33.2 to 77.5 % relative decrease). The negative slopes in urine cotinine levels of the professionals and related workers and clerks were statistically significantly greater than those of the service workers and plant and machine operators and assemblers. CONCLUSIONS: The cotinine concentration in urine among non-smoking worker groups tended to decline from 2009 to 2011. Such a result may be an indirect indicator of the effectiveness of smoking regulation policies including the revision of the National Health Promotion Act.
Classification ; Cotinine* ; Environmental Health ; Female ; Health Promotion ; Humans ; Korea* ; Linear Models ; Male ; National Center for Health Statistics (U.S.) ; Occupations ; Plants ; Sample Size ; Smoke* ; Smoking* ; Tobacco Smoke Pollution

OBJECTIVES: To assess the protective effects of wearing protective devices among the residents and volunteers who participated in the cleanup of the Hebei Spirit oil spill. METHODS: A total of 288 residents and 724 volunteers were surveyed about symptoms, whether they were wearing protective devices and potential confounding variables. The questionnaires were administered from the second to the sixth week following the accident. Spot urine samples were collected and analyzed for metabolites of 4 volatile organic compounds (VOCs), 2 polycyclic aromatic hydrocarbons (PAHs), and 6 heavy metals. The association between the wearing of protective devices and various symptoms was assessed using a multiple logistic regression adjusted for confounding variables. A multiple generalized linear regression model adjusted for the covariates was used to test for a difference in least-square mean concentration of urinary biomarkers between residents who wore protective devices and those who did not. RESULTS: Thirty nine to 98% of the residents and 62-98% of volunteers wore protective devices. Levels of fatigue and fever were higher among residents not wearing masks than among those who did wear masks (odds ratio 4.5; 95% confidence interval 1.23-19.86). Urinary mercury levels were found to be significantly higher among residents not wearing work clothes or boots (p<0.05). CONCLUSIONS: Because the survey was not performed during the initial high-exposure period, no significant difference was found in metabolite levels between people who wore protective devices and those who did not, except for mercury, whose biological half-life is more than 6 weeks.
Adult ; Aged ; Biological Markers/urine ; *Disasters ; Environmental Exposure/*prevention & control ; Environmental Pollutants/*urine ; Female ; Gloves, Protective ; Humans ; Male ; Masks ; Metals, Heavy/urine ; Middle Aged ; Oceans and Seas ; *Petroleum ; Polycyclic Hydrocarbons, Aromatic/urine ; Protective Clothing ; *Protective Devices ; Respiratory Protective Devices ; Shoes ; Volatile Organic Compounds/urine ; Voluntary Workers

Corrected Table 3.